Using VARs and TVP-VARs with many macroeconomic variables

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Abstract

This paper discusses the challenges faced by the empirical macroeconomist and methods for surmounting them. These challenges arise due to the fact that macroeconometric models potentially include a large number of variables and allow for time variation in parameters. These considerations lead to models which have a large number of parameters to estimate relative to the number of observations. A wide range of approaches are surveyed which aim to overcome the resulting problems. We stress the related themes of prior shrinkage, model averaging and model selection. Subsequently, we consider a particular modelling approach in detail. This involves the use of dynamic model selection methods with large TVP-VARs. A forecasting exercise involving a large US macroeconomic data set
illustrates the practicality and empirical success of our approach.
Original languageEnglish
Number of pages34
JournalCentral European Journal of Economic Modelling and Econometrics
Publication statusAccepted/In press - 2012

Keywords

  • bayesian VAR
  • state-space model
  • forecasting
  • time-varying coefficients
  • TVP-VARs
  • macroeconomic variables
  • VARs

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